1. Main points for the three months to February 2017

Estimates from the Labour Force Survey show that, between September to November 2016 and the three months to February 2017, the number of people in work increased, the number of unemployed people fell, and the number of people aged from 16 to 64 not working and not seeking or available to work (economically inactive) also fell.

There were 31.84 million people in work, 39,000 more than for September to November 2016 and 312,000 more than for a year earlier.

The employment rate (the proportion of people aged from 16 to 64 who were in work) was 74.6%, the joint highest since comparable records began in 1971.

There were 1.56 million unemployed people (people not in work but seeking and available to work), 45,000 fewer than for September to November 2016 and 141,000 fewer than for a year earlier.

The unemployment rate was 4.7%, down from 5.1% for a year earlier. It has not been lower since June to August 1975. The unemployment rate is the proportion of the labour force (those in work plus those unemployed) that were unemployed.

There were 8.88 million people aged from 16 to 64 who were economically inactive (not working and not seeking or available to work), 10,000 fewer than for September to November 2016 and 36,000 fewer than for a year earlier.

The inactivity rate (the proportion of people aged from 16 to 64 who were economically inactive) was 21.6%, slightly lower than for September to November 2016 (21.7%) and for a year earlier (21.8%).

Latest estimates show that average weekly earnings for employees in Great Britain in nominal terms (that is, not adjusted for price inflation) increased by 2.3% including bonuses, and by 2.2% excluding bonuses, compared with a year earlier.

Latest estimates show that average weekly earnings for employees in Great Britain in real terms (that is, adjusted for price inflation) increased by 0.2% including bonuses, and by 0.1% excluding bonuses, compared with a year earlier.

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2. Summary of latest labour market statistics

Table 1 and Figure 1 show the latest estimates, for the three months to February 2017, for employment, unemployment and economic inactivity and show how these estimates compare with the previous quarter (September to November 2016) and the previous year (the three months to February 2016). Comparing the estimates for the three months to February 2017 with those for September to November 2016 provides the most robust short-term comparison. See Section 3 of this statistical bulletin for more information.

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3. Things you need to know about this release

Improvements to estimates of real earnings

We are now using our most comprehensive measure of inflation, the Consumer Prices Index including owner occupiers’ housing costs (CPIH), rather than CPI, to estimate real earnings, resulting in revisions to the entire series. As the CPIH series currently commences in 2005 the estimates of real earnings (which previously started in 2000) now start in 2005 and the series shows weekly earnings at constant 2015 prices (rather than constant 2000 prices as shown previously).

Improvements to estimates of vacancies

There have been revisions to estimates of vacancies back to the start of the series in 2001 resulting from the annual review of the seasonal adjustment process and from taking on board late and corrected information from contributors to the Vacancy Survey.

About labour market statuses

Everybody aged 16 or over is either employed, unemployed or economically inactive. The employment estimates include all people in work including those working part-time. People not working are classed as unemployed if they have been looking for work within the last four weeks and are able to start work within the next two weeks. A common misconception is that the unemployment statistics are a count of people on benefits; this is not the case as they include unemployed people not claiming benefits.

Jobless people who have not been looking for work within the last four weeks or who are unable to start work within the next two weeks are classed as economically inactive. Examples of economically inactive people include people not looking for work because they are students, looking after the family or home, because of illness or disability or because they have retired.

Explaining the concepts of employment, unemployment and economic inactivity is available from the National Archives website as a short video.

Making comparisons with earlier data derived from the Labour Force Survey

Estimates of employment, unemployment, economic inactivity, hours worked and redundancies are derived from the Labour Force Survey (LFS), a survey of households. The most robust estimates of short-term movements in these estimates are obtained by comparing the estimates for the three months to February 2017 with the estimates for September to November 2016, which were first published on 18 January 2017. This provides a more robust estimate than comparing with the estimates for the three months to January 2017. This is because the December and January data are included within both estimates, so effectively observed differences are those between the individual months of November 2016 and February 2017. The LFS is sampled such that it is representative of the UK population over a three month period, not for single month periods.

Accuracy and reliability of survey estimates

Most of the figures in this statistical bulletin come from surveys of households or businesses and are therefore estimates rather than precise figures. Further information is available at the Quality and Methodology section of this statistical bulletin.

Where to find explanatory information

A Guide to labour market statistics, which includes a Glossary, is available.

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4. Employment

Things you need to know about employment

Employment measures the number of people in work and differs from the number of jobs because some people have more than one job. Further information is available at Notes for Employment at the end of this section.

A comparison between estimates of employment and jobs is available on our website.

Commentary

The proportion of people aged from 16 to 64 in work is known as the employment rate. Figure 2 shows the employment rates for people, men and women aged from 16 to 64 since comparable records began in 1971. The lowest employment rate for people was 65.6% in 1983, during the economic downturn of the early 1980s. The employment rates for people, men and women have been generally increasing since early 2012. For the latest time period, the three months to February 2017, the employment rate for people was 74.6%, the joint highest since comparable records began in 1971.

Figure 3 looks in more detail at the employment rate for people for the last five years.

For the three months to February 2017, 74.6% of people aged from 16 to 64 were in work, the joint highest employment rate since comparable records began in 1971.

Looking at employment rates by sex, for the three months to February 2017:

  • 79.4% of men aged from 16 to 64 were in work, higher than for a year earlier (79.2%)

  • 69.9% of women aged from 16 to 64 were in work, higher than for a year earlier (69.1%)

The increase in the employment rate for women is partly due to ongoing changes to the State Pension age for women resulting in fewer women retiring between the ages of 60 and 65.

For the three months to February 2017, there were 31.84 million people in work, 39,000 more than for September to November 2016 and 312,000 more than for a year earlier.

Figure 4 shows how the estimates for full-time and part-time employment by sex for the three months to February 2017 compare with those for a year earlier.

Comparing the estimates for type of employment for the three months to February 2017 with those for a year earlier:

  • employees increased by 192,000 to 26.85 million (84.3% of all people in work)

  • self-employed people increased by 114,000 to 4.78 million (15.0% of all people in work)

  • unpaid family workers increased by 17,000 to 117,000 (0.4% of all people in work); see Note 2 at the end of this section for an explanation of the coverage of this series

  • people on government-supported training and employment programmes decreased by 10,000 to 92,000 (0.3% of all people in work); see Note 3 at the end of this section for an explanation of the coverage of this series

Where to find data about employment

Employment estimates are available at Tables 1 and 3 of the PDF version of this statistical bulletin and at datasets A02 SA and EMP01 SA.

International comparisons of employment rates are available at Table 17 of the PDF version of this statistical bulletin and at dataset A10.

Historic estimates of employment back to the 18th century (which do not have National Statistics status) have been published by the Bank of England in the spreadsheet Three centuries of data v2.3 (at worksheets A27 and A28).

Notes for: Employment

  1. Employment consists of employees, self-employed people, unpaid family workers and people on government-supported training and employment programmes.

  2. Unpaid family workers are people who work in a family business who do not receive a formal wage or salary but benefit from the profits of that business.

  3. The government-supported training and employment programmes series does not include all people on these programmes; it only includes people engaging in any form of work, work experience or work-related training who are not included in the employees or self-employed series. People on these programmes not engaging in any form of work, work experience or work-related training are not included in the employment estimates; they are classified as unemployed or economically inactive.

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5. Public and private sector employment (first published on 15 March 2017)

Things you need to know about public and private sector employment

Public sector employment measures the number of people in paid work in the public sector. The public sector comprises central government, local government and public corporations. Estimates of public sector employment are obtained from information provided by public sector organisations.

Private sector employment is estimated as the difference between total employment, sourced from the Labour Force Survey, and public sector employment.

Comparisons of public and private sector employment over time are impacted by changes to the composition of these sectors. For example, if a publicly owned body is privatised, public sector employment will fall and private sector employment will increase by an equivalent amount. This is known as a reclassification effect. At Table 4 of the PDF version of this statistical bulletin and at dataset EMP02 we therefore publish estimates of public and private sector employment excluding the effects of major, but not all, reclassifications alongside estimates of total public and private sector employment.

Commentary

There were 5.44 million people employed in the public sector for December 2016. This was little changed compared with September 2016 and with a year earlier. Public sector employment has been generally falling since December 2009.

There were 26.42 million people employed in the private sector for December 2016. This was 93,000 more than for September 2016 and 324,000 more than for a year earlier.

For December 2016, 17.1% of people in employment worked in the public sector and the remaining 82.9% worked in the private sector.

Figure 5 shows public sector employment as a percentage of all people in employment for the last five years.

Comparisons of public and private sector employment over time are complicated by several large employers moving between the public and private sectors. We therefore publish estimates of public and private sector employment excluding the effects of major reclassifications alongside estimates of total public and private sector employment at Table 4 of the PDF version of this statistical bulletin and at dataset EMP02.

Where to find data about public and private sector employment

Public and private sector employment estimates are available at Tables 4 and 4(1) of the PDF version of this statistical bulletin and at datasets EMP02 and EMP03.

Further information on public sector employment is available in the Public sector employment release.

Historic estimates of public sector employment back to the 19th century (which do not have National Statistics status) have been published by the Bank of England in the spreadsheet Three centuries of data v2.3 (at worksheet A29).

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6. Employment by nationality and country of birth, not seasonally adjusted (first published on 15 February 2017)

Things you need to know about employment by nationality and country of birth

These estimates show the number of people in work and changes in the series show net changes in the number of people in work (the number of people entering employment minus the number of people leaving employment). The number of people entering or leaving employment are larger than the net changes. The estimates therefore do not relate to “new jobs” and cannot be used to estimate the proportion of new jobs that have been filled by UK and non-UK workers. It should also be noted that the estimates of the number of people in work differ from the number of jobs because some people have more than one job.

The estimates are not seasonally adjusted and it is therefore best practice to compare the estimates for October to December 2016 with those for a year earlier rather than with those for July to September 2016.

The estimates for EU nationals and people born in the EU working in the UK, since the start of the time series in 1997, are based on the current membership of the EU.

Commentary

Looking at the estimates by nationality, between October to December 2015 and October to December 2016:

  • UK nationals working in the UK increased by 70,000 to 28.44 million

  • non-UK nationals working in the UK increased by 233,000 to 3.48 million

Looking at changes in non-UK nationals working in the UK between October to December 1997 and October to December 2016:

  • the number of non-UK nationals working in the UK increased from just over 1 million to 3.48 million

  • the proportion of all people working in the UK accounted for by non-UK nationals increased from 3.8% to 10.9%

  • this increase in non-UK nationals working in the UK reflects the admission of several new member states to the European Union (EU)

Looking in more detail at non-UK nationals working in the UK, between October to December 2015 and October to December 2016:

  • non-UK nationals from the EU working in the UK increased by 190,000 to 2.24 million

  • non-UK nationals from outside the EU working in the UK increased by 42,000 to 1.24 million

Figure 6a shows the number of non-UK nationals from EU and non-EU countries working in the UK from October to December 1997 to October to December 2016.

As shown at Figure 6a, since January to March 2009, the number of non-UK nationals from outside the EU working in the UK has been broadly flat but the number of non-UK nationals from EU countries working in the UK has continued to increase.

For October to December 2016, there were 5.54 million people born abroad working in the UK, but the number of non-UK nationals working in the UK was much lower at 3.48 million. This is because the estimates for people born abroad working in the UK include many UK nationals.

Looking at the estimates by country of birth, between October to December 2015 and October to December 2016:

  • UK born people working in the UK decreased by 120,000 to 26.37 million

  • non-UK born people working in the UK increased by 431,000 to 5.54 million

Figure 6b shows the number of people born in EU countries and people born in non-EU countries working in the UK from October to December 1997 to October to December 2016.

Where to find data about employment by nationality and country of birth

Estimates of employment by nationality and country of birth are available at Table 8 of the PDF version of this statistical bulletin and at dataset EMP06.

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7. Actual hours worked

Things you need to know about actual hours worked

Actual hours worked measures the number of hours worked in the economy. Changes in actual hours worked reflect changes in the number of people in employment and the average hours worked by those people.

Commentary

Total hours worked per week were 1.03 billion for the three months to February 2017. This was 13.4 million more than for September to November 2016 and 17.3 million more than for a year earlier.

The increase in total hours worked per week between September to November 2016 and the three months to February 2017 reflects an increase in both the number of people in work (as explained at Section 4 of this statistical bulletin) and in average hours worked per week.

For the three months to February 2017:

  • people worked, on average, 32.4 hours per week, the highest since 2002 largely due to more hours being worked over the Christmas and New Year period compared with recent years

  • people working full-time worked, on average, 37.7 hours per week in their main job, more than for September to November 2016 and for a year earlier

  • people working part-time worked, on average, 16.3 hours per week in their main job, more than for September to November 2016 and for a year earlier

Figure 7 shows total hours worked and the number of people in work, as indices, for the last five years.

Where to find data about hours worked

Hours worked estimates are available at Tables 7 and 7(1) of the PDF version of this statistical bulletin and at datasets HOUR01 SA and HOUR02 SA.

Historic estimates of hours worked back to the 18th century (which do not have National Statistics status) have been published by the Bank of England in the spreadsheet Three centuries of data v2.3 (at worksheet A31).

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8. Workforce jobs (first published on 15 March 2017)

Things you need to know about workforce jobs

Workforce jobs measures the number of filled jobs in the economy. The estimates are mainly sourced from employer surveys. Workforce jobs is a different concept from employment, which is sourced from the Labour Force Survey, as employment is an estimate of people in work and some people have more than one job.

A comparison between estimates of employment and jobs is available on our website.

Commentary

For December 2016 there were 34.62 million workforce jobs, 88,000 more than for September 2016 and 531,000 more than for a year earlier. Figure 8 shows changes in the number of jobs by industrial sector between December 2015 and December 2016.

Looking at a longer-term comparison, between June 1978 (when comparable records began) and December 2016:

  • the proportion of jobs accounted for by the manufacturing and mining and quarrying sectors fell from 26.4% to 7.7%

  • the proportion of jobs accounted for by the services sector increased from 63.2% to 83.6%

Where to find data about workforce jobs

Jobs estimates are available at Tables 5 and 6 of the PDF version of this statistical bulletin and at datasets JOBS01 and JOBS02.

While comparable estimates for workforce jobs by industry begin in 1978, some historical information back to 1841, not comparable with the latest estimates, are available from 2011 Census Analysis, 170 years of industry.

Historic estimates of jobs by industry back to the 19th century (which do not have National Statistics status) have been published by the Bank of England in the spreadsheet Three centuries of data v2.3 (at worksheet A30).

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9. Average weekly earnings

Things you need to know about average weekly earnings

Average weekly earnings measures money paid to employees in Great Britain in return for work done, before tax and other deductions from pay. The estimates do not include earnings of self-employed people. Estimates are available for both total pay (which includes bonuses) and for regular pay (which excludes bonus payments).

Estimates are available in both nominal terms (not adjusted for consumer price inflation) and real terms (adjusted for consumer price inflation). The estimates are not just a measure of pay settlements as they also reflect compositional changes within the workforce. Further information is available at Notes for Average weekly earnings at the end of this section.

Commentary

For February 2017 in nominal terms (that is, not adjusted for price inflation):

  • average regular pay (excluding bonuses) for employees in Great Britain was £478 per week before tax and other deductions from pay, up from £469 per week for a year earlier

  • average total pay (including bonuses) for employees in Great Britain was £509 per week before tax and other deductions from pay, up from £494 per week for a year earlier

Between the three months to February 2016 and the three months to February 2017, in nominal terms, regular pay increased by 2.2%. This was lower than the growth rate between the three months to January 2016 and the three months to January 2017 (2.4%), reflecting lower pay growth across the private sector particularly for wholesaling, retailing, hotels and restaurants.

Between the three months to February 2016 and the three months to February 2017, in nominal terms, total pay increased by 2.3%, the same as between the three months to January 2016 and the three months to January 2017.

Figure 9 compares the annual growth rates for both regular and total pay, in nominal terms, for the last five years.

Looking at longer term movements, average total pay for employees in Great Britain in nominal terms increased from £380 a week in January 2005 to £509 a week in February 2017; an increase of 34.0%. Over the same period the Consumer Prices Index including owner occupiers’ housing costs (CPIH) increased by 30.8%.

Between the three months to February 2016 and the three months to February 2017 in real terms (that is, adjusted for consumer price inflation) regular pay for employees in Great Britain increased by 0.1%, the lowest annual growth rate since July to September 2014 (when regular pay in real terms fell by 0.2% compared with a year earlier).

Between the three months to February 2016 and the three months to February 2017 in real terms (that is, adjusted for consumer price inflation) total pay for employees in Great Britain increased by 0.2%, the lowest growth rate since August to October 2014 (0.1%).

A more detailed analysis of earnings growth in real terms is available at Analysis of real earnings.

Where to find data about average weekly earnings

Estimates of average weekly earnings in nominal terms (that is, not adjusted for consumer price inflation) are available at Tables 13, 14 and 15 of the PDF version of this statistical bulletin and at datasets EARN01, EARN02 and EARN03.

Estimates of average weekly earnings in real terms (that is, adjusted for consumer price inflation) are available at Table 16 of the PDF version of this statistical bulletin and at dataset EARN01.

While comparable records for average weekly earnings start in 2000, modelled estimates of average weekly earnings in nominal terms back to 1963 (which do not have National Statistics status) are available at dataset EARN02.

Estimates back to 1750 (which do not have National Statistics status) have been published by the Bank of England in the spreadsheet Three centuries of data v2.3 (at worksheet A26).

Where to find more information about earnings

Analysis of real earnings is available on our website.

An article looking at bonus payments is published annually. The most recent edition of this article was published on 15 September 2016.

The Annual Survey of Hours and Earnings (ASHE), published on 26 October 2016, provides more detailed data for 2016.

Notes for: Average Weekly Earnings

  1. The estimates relate to Great Britain and include salaries but not unearned income, benefits in kind or arrears of pay.

  2. As well as pay settlements, the estimates reflect bonuses, changes in the number of paid hours worked and the impact of employees paid at different rates joining and leaving individual businesses. The estimates also reflect changes in the overall structure of the workforce; for example, more low paid jobs in the economy would have a downward effect on the earnings growth rate.

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10. Labour disputes (not seasonally adjusted)

Things you need to know about labour disputes

Labour disputes estimates measure strikes connected with terms and conditions of employment.

Commentary

For February 2017:

  • there were 21,000 working days lost from 14 stoppages

  • 3,000 people took strike action

The number of working days lost are at historically low levels when looking at the long-run monthly time series back to the 1930s.

Since monthly records began in December 1931:

  • the highest cumulative 12 month estimate for working days lost was 32.2 million for the 12 months to April 1980

  • the lowest cumulative 12 month estimate for working days lost was 143,000 for the 12 months to March 2011

For the 12 months ending February 2017:

  • there were 322,000 working days lost from 96 stoppages

  • 156,000 people took strike action

Figure 10 shows an industrial breakdown of the 322,000 working days lost for the 12 months ending February 2017. A more detailed industrial breakdown is available at datasets LABD02 and LABD03.

Where to find data about labour disputes

Labour disputes estimates are available at Table 18 of the PDF version of this statistical bulletin and at dataset LABD01.

Where to find more information about labour disputes

The labour disputes annual article provides more detailed information. The most recent edition of this article was published on 2 August 2016.

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11. Unemployment

Things you need to know about unemployment

Unemployment measures people without a job who have been actively seeking work within the last four weeks and are available to start work within the next two weeks.

The unemployment rate is not the proportion of the total population who are unemployed. It is the proportion of the economically active population (those in work plus those seeking and available to work) who are unemployed. This follows guidelines specified by the International Labour Organisation and it ensures that UK unemployment statistics are broadly comparable with those published by other countries.

Commentary

The proportion of economically active people aged 16 and over who are out of work and seeking work is known as the unemployment rate. As shown at Figure 11 (which shows unemployment rates for people, men and women), the lowest unemployment rate for people recorded since comparable records began in 1971 was 3.4% in late 1973 to early 1974 and the highest rate, 11.9%, was recorded in 1984 during the downturn of the early 1980s. The unemployment rate for people for the latest time period, the three months to February 2017, was 4.7%. It has not been lower since June to August 1975.

Figure 12 looks in more detail at the unemployment rates for the last five years.

For the three months to February 2017:

  • the unemployment rate for people was 4.7%; it has not been lower since June to August 1975

  • the unemployment rate for men was 4.8%, it has not been lower since April to June 1979

  • the unemployment rate for women was 4.5%; it has not been lower since August to October 2005

For the three months to February 2017, there were:

  • 1.56 million unemployed people, 45,000 fewer than for September to November 2016 and 141,000 fewer than for a year earlier

  • 853,000 unemployed men, 30,000 fewer than for September to November 2016 and 76,000 fewer than for a year earlier

  • 706,000 unemployed women, 15,000 fewer than for September to November 2016 and 65,000 fewer than for a year earlier

Looking at unemployment by how long people have been out of work and seeking work, for the three months to February 2017, there were:

  • 920,000 people who had been unemployed for up to 6 months, 44,000 fewer than for a year earlier

  • 250,000 people who had been unemployed for between 6 and 12 months, 19,000 fewer than for a year earlier

  • 389,000 people who had been unemployed for over 12 months, 79,000 fewer than for a year earlier

Where to find data about unemployment

Unemployment estimates for the UK are available at Table 9 of the PDF version of this statistical bulletin and at dataset UNEM01 SA.

Historic estimates of unemployment back to the 18th century (which do not have National Statistics status) have been published by the Bank of England in the spreadsheet Three centuries of data v2.3 (at worksheets A27 and A28).

International comparisons of unemployment rates are available at Table 17 of the PDF version of this statistical bulletin and at dataset A10.

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12. Economic inactivity

Things you need to know about economic inactivity

Economically inactive people are not in employment but do not meet the internationally accepted definition of unemployment because they have not been seeking work within the last four weeks and/or they are unable to start work within the next two weeks.

Commentary

The proportion of people, aged from 16 to 64, not in work and neither seeking nor available to work is known as the economic inactivity rate. Figure 13 shows that, since comparable records began in 1971, the economic inactivity rate for people has been generally falling (although it increased during economic downturns) due to a gradual fall in the economic inactivity rate for women. The economic inactivity rate for men has been gradually rising.

For the three months to February 2017:

  • the economic inactivity rate for people was 21.6%

  • the economic inactivity rate for men was 16.5%

  • the economic inactivity rate for women was 26.7%

Figure 14 looks in more detail at the economic inactivity rate for people since comparable records began in 1971. The economic inactivity rate for people increased during the downturn of the early 1980s reaching a record high of 25.9% in 1983. As the economy improved in the late 1980s, it resumed its downward path before the economic downturn of the early 1990s drove it back up again. Following an increase in the economic inactivity rate during the economic downturn of 2008 to 2009, it again resumed a generally downward path. For the latest time period, the three months to February 2017, the economic inactivity rate for people was 21.6%.

For the three months to February 2017, there were 8.88 million people aged from 16 to 64 not in work and neither seeking nor available to work (known as economically inactive). This was 10,000 fewer than for September to November 2016 and 36,000 fewer than for a year earlier.

Looking in more detail at the 8.88 million people aged from 16 to 64 who were economically inactive for the three months to February 2017, the 2 largest categories were students and people looking after the family or home (each of which accounted for around a quarter of the total):

  • there were 2.33 million people who were not looking for work because they were studying, 73,000 more than for a year earlier

  • there were 2.21 million people (of which 1.95 million were women) who were not looking for work because they were looking after the family or home, 35,000 fewer than for a year earlier

The third and fourth largest categories were long-term sick (22.3% of the total) and retired (13.2% of the total):

  • there were 1.98 million people who were not looking for work due to long-term sickness, 98,000 fewer than for a year earlier

  • there were 1.17 million people who were not looking for work because they had retired, little changed compared with a year earlier

As shown at Figure 15, which shows the four largest categories of economic inactivity for the last five years, the number of people younger than 65 in the retired category has been generally falling since late 2011. This is largely due to ongoing changes to the State Pension age for women resulting in fewer women retiring between the ages of 60 and 65.

Where to find data about economic inactivity

Economic inactivity estimates are available at Tables 1 and 11 of the PDF version of this statistical bulletin and at datasets A02 SA and INAC01 SA.

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13. Young people in the labour market

Things you need to know about young people in the labour market

This section looks at people aged from 16 to 24. It is a common misconception that all people in full-time education are classified as economically inactive. This is not the case as people in full-time education are included in the employment estimates if they have a part-time job and are included in the unemployment estimates if they are seeking part-time work.

Commentary

For the three months to February 2017, for people aged from 16 to 24, there were:

  • 3.93 million people in work (including 932,000 full-time students with part-time jobs)

  • 558,000 unemployed people (including 193,000 full-time students looking for part-time work)

  • 2.66 million economically inactive people, most of whom (2.04 million) were full-time students

Figure 17 shows how the latest estimates, for the three months to February 2017, for employment, unemployment and economic inactivity for people aged from 16 to 24 compare with the previous quarter (September to November 2016) and the previous year (the three months to February 2016).

For the three months to February 2017, the unemployment rate for 16 to 24 year olds was 12.4%, lower than for a year earlier (13.7%).

The unemployment rate for those aged from 16 to 24 has been consistently higher than that for older age groups. Since comparable records began in 1992:

  • the lowest youth unemployment rate was 11.6% for March to May 2001

  • the highest youth unemployment rate was 22.5% for late 2011

Between March to May 1992 (when comparable records began) and the three months to February 2017 the proportion of people aged from 16 to 24 who were in full-time education increased substantially from 26.2% to 44.4%. This increase in the number of young people going into full-time education has reduced the size of the economically active population (those in work plus those seeking and available to work) and therefore increased the unemployment rate (because the unemployment rate is the proportion of the economically active population who are unemployed).

Where to find data about young people in the labour market

Estimates for young people in the labour market are available at Table 12 of the PDF version of this statistical bulletin and at dataset A06 SA.

Where to find more information about young people in the labour market

Estimates for young people who were Not in Education, Employment or Training (NEET) for October to December 2016 were published on 23 February 2017.

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14. Redundancies

Things you need to know about redundancies

The redundancies estimates measure the number of people who were made redundant or who took voluntary redundancy in the three months before the Labour Force Survey interviews.

Commentary

For the three months to February 2017, 106,000 people had become redundant in the three months before the Labour Force Survey interviews. This was 16,000 fewer than for September to November 2016 and 6,000 fewer than for a year earlier.

Figure 18 shows the number of redundancies since comparable records began in 1995.

Where to find data about redundancies

Redundancies estimates are available at Tables 22 and 23 of the PDF version of this statistical bulletin and at datasets RED01 SA and RED02.

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15. Vacancies

Things you need to know about vacancies

Vacancies are defined as positions for which employers are actively seeking to recruit outside their business or organisation.

Commentary

There were 767,000 job vacancies for January to March 2017. This was:

  • 16,000 more than for October to December 2016

  • 14,000 more than for a year earlier

  • The highest since comparable records began in 2001

Figure 19 shows the number of job vacancies since comparable records began in 2001.

There were 678,000 job vacancies in the services sectors for January to March 2017, accounting for 88.4% of all vacancies. Looking at services in more detail, the sectors with the largest number of job vacancies were wholesaling, retailing and repair of motor vehicles (139,000) and human health and social work (118,000).

Where to find data about vacancies

Vacancies estimates are available at Tables 19, 20 and 21 of the PDF version of this statistical bulletin and at datasets VACS01, VACS02 and VACS03.

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16. Upcoming changes and future publication dates

Developments planned for next month’s release

There will be revisions to estimates derived from the Labour Force Survey (including estimates of employment, unemployment and economic inactivity) back to May to July 2012, resulting from taking on board the latest population estimates and a review of the seasonal adjustment process.

There will also be revisions to estimates of Average Weekly Earnings back to the start of the series in 2000 due to improvements to the estimation of earnings of employees of small businesses and a review of the seasonal adjustment process. An article explaining these improvements to Average Weekly Earnings was published on our website on 29 March 2017.

Future publication dates

Publication dates up to the end of 2017 are:

17 May 2017
14 June 2017
12 July 2017
16 August 2017
13 September 2017
18 October 2017
15 November 2017
13 December 2017

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18. Quality and methodology

Revisions

Estimates for the most recent time periods are subject to revision due to the receipt of late and corrected responses to business surveys and revisions to seasonal adjustment factors which are re-estimated every month. Estimates are subject to longer run revisions, on an annual basis, resulting from reviews of the seasonal adjustment process. Estimates derived from the Labour Force Survey (a survey of households) are usually only revised once a year. Revisions to estimates derived from other sources are usually minor and are commented on in the statistical bulletin if this is not the case. Further information is available in the labour market statistics revisions policy.

One indication of the reliability of the main indicators in this statistical bulletin can be obtained by monitoring the size of revisions. Datasets EMP05, UNEM04, JOBS06 and CLA03 record the size and pattern of revisions over the last five years. These indicators only report summary measures for revisions. The revised data itself may be subject to sampling or other sources of error. Our standard presentation is to show five years worth of revisions (60 observations for a monthly series, 20 for a quarterly series).

Accuracy of the statistics: estimating and reporting uncertainty

Most of the figures in this statistical bulletin come from surveys of households or businesses. Surveys gather information from a sample rather than from the whole population. The sample is designed to allow for this, and to be as accurate as possible given practical limitations such as time and cost constraints, but results from sample surveys are always estimates, not precise figures. This means that they are subject to some uncertainty. This can have an impact on how changes in the estimates should be interpreted, especially for short-term comparisons.

We can illustrate the level of uncertainty (also called “sampling variability”) around a survey estimate by defining a range around the estimate (known as a “confidence interval”) within which we think the real value that the survey is trying to measure lies. Confidence intervals are typically defined so that we can say we are 95% confident the true value lies within the range – in which case we refer to a “95% confidence interval”.

The number of people unemployed for the three months to February 2017 was estimated at 1,559,000, with a stated 95% confidence interval of +/- 73,000. This means that we are 95% confident that the true number of unemployed people was between 1,486,000 and 1,632,000. Again, the best estimate from the survey was that the number of unemployed people was 1,559,000.

As well as calculating precision measures around the numbers and rates obtained from the survey, we can also calculate them for changes in the numbers. For example, for the three months to February 2017, the estimated change in the number of unemployed people since September to November 2016 was a fall of 45,000 with a 95% confidence interval of +/- 79,000. This means that we are 95% confident the actual change in unemployment was somewhere between an increase of 34,000 and a fall of 124,000, with the best estimate being a fall of 45,000. As the estimated fall in unemployment of 45,000 is smaller than 79,000, the estimated fall in unemployment is said to be “not statistically significant”.

In general, changes in the numbers (and especially the rates) reported in this statistical bulletin between three month periods are small, and are not usually greater than the level that is explainable by sampling variability. In practice, this means that small, short-term movements in reported rates (for example within +/- 0.3 percentage points) should be treated as indicative, and considered alongside medium and long-term patterns in the series and corresponding movements in administrative sources, where available, to give a fuller picture.

Where to find data about uncertainty and reliability

Dataset A11 shows sampling variabilities for estimates derived from the Labour Force Survey.

Dataset JOBS07 shows sampling variabilities for estimates of workforce jobs.

The sampling variability of the three month average vacancies level is around +/- 1.5% of that level.

Sampling variability information for average weekly earnings growth rates are available from the “Sampling Variability” worksheets within datasets EARN01 and EARN03.

Seasonal adjustment and uncertainty

Like many economic indicators, the labour market is affected by factors that tend to occur at around the same time every year; for example, school leavers entering the labour market in July and whether Easter falls in March or April. In order to compare movements other than annual changes in labour market statistics, such as since the previous quarter or since the previous month, the data are seasonally adjusted to remove the effects of seasonal factors and the arrangement of the calendar. All estimates discussed in this statistical bulletin are seasonally adjusted except where otherwise stated. While seasonal adjustment is essential to allow for robust comparisons through time, it is not possible to estimate uncertainty measures for the seasonally adjusted series.

Quality and Methodology Information documents

The Quality and Methodology Information documents contain important information on:

  • the strengths and limitations of the data and how it compares with related data

  • users and uses of the data

  • how the output was created

  • the quality of the output including the accuracy of the data

Labour Force Survey Quality and Methodology Information

Labour Force Survey performance and quality monitoring reports

Vacancy Survey Quality and Methodology Information

Workforce Jobs Quality and Methodology Information

Average weekly earnings (AWE) Quality and Methodology Information

Labour Disputes Quality and Methodology Information

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